JND mask adaptation for wavelet domain watermarking

One of the most challenging issues for watermarkers is to tune the strength of their watermark embedding. The strength is usually an alpha parameter which is increased until a reasonable trade-off between invisibility and robustness is achieved. The watermarking community needs efficient just noticeable difference (JND) masks to optimally embed the watermarks. The Fourier transform is particularly adapted to the human visual system (HVS) modeling. In this work, we evaluate the usability of the JND mask in the wavelet domain. The use of the mask in the DWT domain involves some approximations. We will see here that the HVS decomposition and the wavelet decomposition do not perfectly fit altogether. The efficiency of the so obtained mask is tested both in terms of invisibility and robustness.